D2D communication system energy efficiency optimization method, device, equipment and storage medium

Abstract

The invention provides a D2D communication system energy efficiency optimization method, apparatus and device, and a storage medium. The method comprises the steps of constructing an IRS-assisted D2D communication network model; dividing the communication process of the D2D communication network model in the current time slot into a first stage and a second stage; solving an energy efficiency optimization problem to obtain a first optimal D2D transmission precoding in a first stage, a second optimal D2D transmission precoding in a second stage, an optimal phase shift response vector of a reflection element in the IRS and an optimal energy collection duration of the IRS in the first stage; and determining the maximum energy efficiency of the D2D communication system based on the plurality of optimal parameters. According to the D2D communication system energy efficiency optimization method provided by the invention, the problem of D2D communication network energy efficiency maximization under the condition of inaccurate channel state information is solved by combining power control, passive beam forming design and energy acquisition time scheduling, and the energy utilization rate of the D2D communication system is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of wireless communications, and in particular to a method, device, equipment and storage medium for optimizing energy efficiency of a D2D communication system. Background Art

[0002] Device-to-Device (D2D) communication allows adjacent users to reuse the same frequency band network resources to improve communication quality. According to the spectrum utilization method, it can be divided into in-band D2D and out-band D2D. The former has mutual interference between cellular users and D2D users, while the latter eliminates the interference caused by cellular networks because the frequency is only shared between D2D users. It brings more flexibility and possibilities to Internet applications, involving industrial, scientific, medical and other scenarios. However, due to co-channel reuse, interference management is still a thorny issue, especially in IoT scenarios with a large number of D2D users.

[0003] As a new generation of communication technology, the Intelligent Reflection Surface (IRS) can dynamically adjust the amplitude and phase of the incident signal, adjust the path of the incident signal, build a programmable wireless propagation environment, and effectively reduce the interference caused by co-channel multiplexing. The passive characteristics of IRS make it have the advantages of low power consumption and low cost, but it also brings the problem of difficult channel estimation of the reflection link, thus affecting the energy efficiency of the D2D communication system. Summary of the invention

[0004] The present invention provides a D2D communication system energy efficiency optimization method, device, equipment and storage medium, which are used to solve the problem that the energy efficiency of the D2D communication system is affected by the channel uncertainty in the IRS-assisted D2D communication system.

[0005] In a first aspect, the present invention provides a method for optimizing energy efficiency of a D2D communication system, comprising: Construct an IRS-assisted D2D communication network model; The D2D communication process of the D2D communication network model in the current time slot is divided into a first stage and a second stage; the first stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter reaches the D2D receiver through a direct link, and the IRS collects energy from the radio frequency signal; the second stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter reaches the D2D receiver through a direct link and an IRS reflection link; Solving the energy efficiency optimization problem in the D2D communication network model, obtaining a first optimal D2D transmit precoding in the first stage, a second optimal D2D transmit precoding in the second stage, an optimal phase shift response vector of a reflective element in an IRS, and an optimal energy collection duration of the IRS in the first stage; The maximum energy efficiency of the D2D communication system is determined based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector, and the optimal energy collection duration.

[0006] In one embodiment, solving the energy efficiency optimization problem in the D2D communication network model to obtain the first optimal D2D transmit precoding in the first stage, the second optimal D2D transmit precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS, and the optimal energy collection duration of the IRS in the first stage include: The energy efficiency optimization problem in the D2D communication network model is respectively converted into a first optimization sub-problem, a second optimization sub-problem, a third optimization sub-problem and a fourth optimization sub-problem; the first optimization sub-problem is used to optimize the first D2D transmission precoding in the first stage given the second D2D transmission precoding in the second stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the second optimization sub-problem is used to optimize the second D2D transmission precoding in the second stage given the first D2D transmission precoding in the first stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the third optimization sub-problem is used to optimize the phase shift response vector of the reflection element in the IRS given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the energy collection time of the IRS in the first stage; the fourth optimization sub-problem is used to optimize the energy collection time of the IRS in the first stage given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the phase shift response vector of the reflection element in the IRS; Solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a first optimal D2D transmit precoding in the first stage; Solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a second optimal D2D transmit precoding in the second stage; Solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initial energy collection duration to obtain an optimal phase shift response vector of a reflective element in the IRS; Based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector, the fourth optimization sub-problem is solved to obtain the optimal energy collection duration of the IRS in the first stage.

[0007] In one embodiment, solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain the first optimal D2D transmit precoding in the first stage includes: Obtaining, through initialization, a first initial D2D transmission precoding in the first stage, a second initial D2D transmission precoding in the second stage, an initial phase shift response vector of a reflective element in an IRS, an initial energy collection duration of the IRS in the first stage, a preset threshold, and a maximum number of iterations; Determine the first initial D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as first input data of the D2D communication network model; Under the conditions of satisfying the first constraint, the second constraint and the third constraint, the first initial D2D transmission precoding is updated according to the first input data and the first objective function; the first constraint is used to constrain the total system rate at the D2D receiver in the first stage; the second constraint is used to constrain the transmission power of the D2D transmitter in the first stage; the third constraint is used to constrain the energy collected by the IRS to be greater than or equal to the power consumption when the IRS is reflected; the first objective function is used to solve the first optimization subproblem; Iteratively execute the step of updating the first initial D2D transmit precoding according to the first input data and the first objective function while satisfying the first constraint condition, the second constraint condition and the third constraint condition, until the first objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the first optimal D2D transmit precoding in the first stage.

[0008] In one embodiment, solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain the second optimal D2D transmit precoding in the second stage includes: Determine the first optimal D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as second input data of the D2D communication network model; Under the condition that the fourth constraint and the fifth constraint are satisfied, the second initial D2D transmit precoding is updated according to the second input data and the second objective function; the fourth constraint is used to constrain the total system rate at the D2D receiver in the second stage; the fifth constraint is used to constrain the transmit power of the D2D transmitter in the second stage; the second objective function is used to solve the second optimization subproblem; Iteratively execute the step of updating the second initial D2D transmit precoding according to the second input data and the second objective function while satisfying the fourth constraint and the fifth constraint, until the second objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, to obtain the second optimal D2D transmit precoding in the second stage.

[0009] In one embodiment, solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initial energy collection duration to obtain the optimal phase shift response vector of the reflective element in the IRS includes: Determine the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as third input data of the D2D communication network model; Under the condition of satisfying the sixth constraint, updating the initial phase shift response vector according to the third input data and the third objective function; the sixth constraint is used to constrain the phase shift of the reflective element in the IRS; the third objective function is used to solve the third optimization sub-problem; Iteratively executing the step of updating the initial phase shift response vector according to the third input data and the third objective function while satisfying the sixth constraint condition until the third objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the optimal phase shift response vector of the reflective element in the IRS.

[0010] In one embodiment, solving the fourth optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the optimal phase shift response vector to obtain the optimal energy collection duration of the IRS in the first stage includes: Determining the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the initial energy collection duration as fourth input data of the D2D communication network model; Under the conditions of satisfying the third constraint and the seventh constraint, the initial energy collection duration is updated according to the fourth input data and the fourth objective function to obtain the optimal energy collection duration of the IRS in the first stage; the seventh constraint is used to constrain the IRS energy collection duration to not exceed one time slot; the fourth objective function is used to solve the fourth optimization subproblem.

[0011] In one embodiment, the maximum energy efficiency is determined by the following formula: ; in, represents the energy efficiency of the D2D communication system; K represents the number of D2D transmitters or the number of D2D receivers; Indicates that in the first stage, the D2D receiver The signal-to-interference-noise ratio at Indicates that in the second stage, the D2D receiver The signal-to-interference-noise ratio at Indicates that in the first stage, the D2D transmitter The transmission power; Indicates that in the second stage, the D2D transmitter The transmission power; Indicates the basic circuit power consumption of the D2D device; Indicates that in the first stage, the D2D receiver The interference plus noise power at Indicates D2D receiver To D2D transmitter A direct link channel; Indicates that in the second stage, the D2D receiver The interference plus noise power at represents the phase shift response vector of the reflective element in the IRS in the second stage; Indicates D2D receiver To D2D transmitter Cascade link channel.

[0012] In a second aspect, the present invention further provides a D2D communication system energy efficiency optimization device, comprising: A model building module, used to build an IRS-assisted D2D communication network model; A D2D communication division module is used to divide the D2D communication process of the D2D communication network model in the current time slot into a first stage and a second stage; the first stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link, and the IRS collects energy from the radio frequency signal; the second stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link and an IRS reflection link; An optimization problem solving module, used to solve the energy efficiency optimization problem in the D2D communication network model, and obtain a first optimal D2D transmit precoding in the first stage, a second optimal D2D transmit precoding in the second stage, an optimal phase shift response vector of a reflective element in an IRS, and an optimal energy collection duration of the IRS in the first stage; The energy efficiency maximization module is used to determine the maximum energy efficiency of the D2D communication system based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the optimal energy collection duration.

[0013] In a third aspect, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of any of the above-mentioned methods for optimizing energy efficiency of a D2D communication system are implemented.

[0014] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any of the above-mentioned methods for optimizing energy efficiency of a D2D communication system are implemented.

[0015] The D2D communication system energy efficiency optimization method, device, equipment and storage medium provided by the present invention construct an IRS-assisted D2D communication network model, and by introducing a low-power IRS in the D2D communication network, the desired signal is enhanced and the interference signal is suppressed at the receiving end. The D2D communication process of the model in the current time slot is further divided into two stages for distinguishing the IRS energy collection stage and the signal reflection stage. By solving the energy efficiency optimization problem of the model, the first optimal transmit precoding, the second optimal transmit precoding, the optimal phase shift response vector and the optimal energy collection duration are obtained, and the system energy efficiency is maximized based on these optimal parameters. The energy efficiency maximization problem of the D2D communication network under the condition of inaccurate channel state information is solved by joint power control, passive beamforming design and energy collection time scheduling, thereby significantly improving the energy utilization rate of the D2D communication system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a flow chart of the D2D communication system energy efficiency optimization method provided by the present invention.

[0018] Figure 2 It is a schematic diagram of the IRS-assisted D2D communication network model provided by the present invention.

[0019] Figure 3 It is a structural schematic diagram of the D2D communication system energy efficiency optimization device provided by the present invention.

[0020] Figure 4 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0021] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] The terms "first", "second", etc. in the present invention are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that the terms used in this way can be interchangeable where appropriate, so that the embodiments of the present invention can be implemented in an order other than those illustrated or described herein.

[0023] Combine the following Figure 1-Figure 4 The present invention describes a D2D communication system energy efficiency optimization method, device, equipment and storage medium provided by the present invention.

[0024] It should be noted that the D2D communication system energy efficiency optimization method provided by the embodiment of the present invention is implemented based on the D2D communication system energy efficiency optimization device. The D2D communication system energy efficiency optimization method provided by the present invention realizes the enhancement of the desired model and the suppression of interference signals at the receiving end by introducing a low-power intelligent reflection surface in the D2D network. Due to the passive characteristics of the intelligent reflection surface, it is difficult to obtain accurate channel estimation of the reflection link. In view of this channel uncertainty, a robust energy efficiency maximization algorithm based on alternating optimization is designed, and the Dinkelbach method, Lagrange dual transformation, quadratic transformation and S process are used to solve the transmission precoding, and the penalty concave-convex process technology is used to solve the optimal phase shift response of the intelligent reflection surface, and the closed-form expression of the optimal energy collection time is theoretically derived. Therefore, through the alternating optimization method, significant progress can be made in the study of energy efficiency, frequency efficiency and communication reliability, providing a new idea for improving the performance of D2D communication networks.

[0025] The embodiment of the present invention describes the D2D communication system energy efficiency optimization method by taking the D2D communication system energy efficiency optimization device in the D2D communication system energy efficiency optimization device as an execution subject as an example.

[0026] Combination Figure 1-Figure 2 , Figure 1 is a flow chart of a D2D communication system energy efficiency optimization method provided by the present invention, Figure 2 It is a schematic diagram of the IRS-assisted D2D communication network model provided by the present invention.

[0027] like Figure 1 As shown, the method includes the following: Step 101: construct an IRS-assisted D2D communication network model; Step 102: dividing the D2D communication process of the D2D communication network model in the current time slot into a first stage and a second stage; Step 103, solving the energy efficiency optimization problem in the D2D communication network model, obtaining the first optimal D2D transmit precoding in the first stage, the second optimal D2D transmit precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS, and the optimal energy collection duration of the IRS in the first stage; Step 104: Determine the maximum energy efficiency of the D2D communication system based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector, and the optimal energy collection duration.

[0028] Specifically, if Figure 2 As shown, Figure 2A network model studied in an embodiment of the present invention is shown, namely a D2D communication network model that can assist a D2D communication network system through an IRS that collects energy. It should be noted that in order to eliminate interference caused by a cellular network, the D2D communication network system and the D2D communication network model both use out-of-band D2D for communication.

[0029] like Figure 2 , the IRS has Reflective elements, auxiliary D2D Transmitter (DT) and IRS collects energy from the RF signal emitted by the D2D transmitter and assists D2D communication based on the time-slicing protocol.

[0030] That is, the D2D communication process of the D2D communication network model in the current time slot is divided into the first stage and the second stage. In this embodiment, a time slot is defaulted to 1. Specifically: In the first stage, DT transmits a radio frequency signal to communicate directly with DR, and all reflective elements of IRS are used to collect energy, and the duration is In the second stage, IRS collects enough energy to perform passive beamforming to assist D2D communication, which can enhance D2D communication. The RF signal transmitted by DT is transmitted to DR through the direct link and IRS reflection link for a duration of .

[0031] definition They are DTs are precoded in the first and second phases of transmission. Due to the passive reflection characteristics of IRS, It is difficult to obtain an accurate channel estimate for the cascaded channel between . Therefore, we define Direct link channel It is the perfect channel. Cascade Channel is an imperfect channel, where and They are link, Based on the bounded channel state information error model, the cascade channel can be further expressed as ,in, is the estimated value of the channel state information, Estimate the error for the unknown channel state information and satisfy , represents the radius of the uncertainty region.

[0032] definition represents the IRS phase shift response matrix, where , represents the IRS phase shift response vector, N represents the number of reflective elements in the IRS, Indicates The phase shift of the reflective element, = ...

[0033] In the first stage, the received signal at the IRS is expressed as The received signal at is expressed as in, express The transmission signal, express The transmission power, symbol represents a symbolic variable with zero mean and unit variance, represents additive Gaussian white noise with zero mean and unit variance distribution, express link, express direct link.

[0034] The energy harvesting power when IRS harvests energy is expressed as: ; (1) in, represents the linear energy collection efficiency, represents the received power at the IRS, Indicates saturation power.

[0035] Therefore, the energy collected by IRS can be expressed as in, is the upper limit of energy storage of IRS.

[0036] In the IRS energy harvesting phase, The signal-to-interference-noise ratio at ,in, express The interference plus noise power at .

[0037] Furthermore, in the IRS energy harvesting phase, The total system rate at During the IRS signal reflection phase, The received signal at is expressed as The signal-to-interference-noise ratio at can be expressed as ,in, represents the interference plus noise term.

[0038] The total system rate at can be expressed as The resolution of each reflective element in IRS is bit, its phase shift space is expressed as .

[0039] definition Represents the power consumption of each reflector, so the power consumption calculation formula of IRS is: Obviously, to ensure that the IRS can continue to work during the signal reflection phase, the inequality needs to be satisfied .

[0040] Based on the D2D communication network model of the above D2D communication system, the following D2D communication system energy efficiency maximization problem can be constructed. The system energy efficiency can be improved by combining power control, passive beamforming design and energy collection time scheduling. The system energy efficiency maximization problem is constructed as follows: is the objective function of the system energy efficiency maximization problem, where represents the energy efficiency of the D2D communication system; Indicates the number of D2D transmitters or the number of D2D receivers; Indicates that the D2D receiver in the first phase The signal-to-interference-noise ratio at Indicates that the D2D receiver in the second phase The signal-to-interference-noise ratio at Indicates that the D2D transmitter in the first phase The transmission power; Indicates that the D2D transmitter in the second phase The transmission power; Indicates the basic circuit power consumption of IRS.

[0041] is the first constraint, which is used to constrain the total system rate at the D2D receiver during the energy collection phase, where: express The minimum receiving rate during the energy harvesting phase; is the second constraint condition, which is used to constrain the transmission power of the D2D transmitter during the energy collection phase, where: express Maximum transmit power during the energy harvesting phase; The third constraint is used to constrain the energy collected by the IRS to be greater than or equal to the power consumption of the IRS when reflecting, that is, the discrete phase shift constraint; is the fourth constraint condition, which is used to constrain the total system rate at the D2D receiver during the signal reflection phase, where: Table representation The minimum receiving rate during the signal reflection phase, represents the channel state information boundary error; is the fifth constraint condition, which is used to constrain the transmission power of the D2D transmitter in the signal reflection phase, wherein: express Maximum transmit power during the signal reflection phase; is the sixth constraint, used to constrain the phase shift of the reflective element in the IRS; It is the seventh constraint, which is used to constrain the IRS energy collection duration to not exceed one time slot.

[0042] By solving the energy efficiency optimization problem in the D2D communication network model, the first optimal D2D transmit precoding in the first stage, the second optimal D2D transmit precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS and the optimal energy collection duration of the IRS in the first stage are obtained.

[0043] After solving the first optimal D2D transmission precoding, the second optimal D2D transmission precoding, the optimal phase shift response vector and the optimal energy collection time, use them as known data through the formula By performing calculations, the maximum energy efficiency of the D2D communication system can be obtained, thereby maximizing the D2D communication system and energy efficiency.

[0044] The D2D communication system energy efficiency optimization method provided by the present invention constructs an IRS-assisted D2D communication network model, and realizes the enhancement of the desired signal and the suppression of the interference signal at the receiving end by introducing a low-power IRS in the D2D communication network. The D2D communication process of the model in the current time slot is further divided into two stages for distinguishing the IRS energy collection stage and the signal reflection stage. By solving the energy efficiency optimization problem of the model, the first optimal transmit precoding, the second optimal transmit precoding, the optimal phase shift response vector and the optimal energy collection duration are obtained, and the system energy efficiency is maximized based on these optimal parameters. The energy efficiency maximization problem of the D2D communication network under the condition of inaccurate channel state information is solved by joint power control, passive beamforming design and energy collection time scheduling, thereby significantly improving the energy utilization rate of the D2D communication system.

[0045] In some embodiments, solving the energy efficiency optimization problem in the D2D communication network model to obtain the first optimal D2D transmit precoding in the first stage, the second optimal D2D transmit precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS, and the optimal energy collection duration of the IRS in the first stage include: The energy efficiency optimization problem in the D2D communication network model is respectively converted into a first optimization sub-problem, a second optimization sub-problem, a third optimization sub-problem and a fourth optimization sub-problem; the first optimization sub-problem is used to optimize the first D2D transmission precoding in the first stage given the second D2D transmission precoding in the second stage, the phase shift response vector of the reflective element in the IRS and the energy collection time of the IRS in the first stage; the second optimization sub-problem is used to optimize the second D2D transmission precoding in the second stage given the first D2D transmission precoding in the first stage, the phase shift response vector of the reflective element in the IRS and the energy collection time of the IRS in the first stage; the third optimization sub-problem is used to optimize the phase shift response vector of the reflective element in the IRS given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the energy collection time of the IRS in the first stage; the fourth optimization sub-problem is used to optimize the first D2D transmission precoding in the first stage given the second D2D transmission precoding in the second stage and the energy collection time of the IRS in the first stage In the case of a D2D transmit precoding, a second D2D transmit precoding in the second stage, and a phase shift response vector of a reflective element in the IRS, the energy collection duration of the IRS in the first stage is optimized; based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration, the first optimization sub-problem is solved to obtain the first optimal D2D transmit precoding in the first stage; based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration, the second optimization sub-problem is solved to obtain the second optimal D2D transmit precoding in the second stage; based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initial energy collection duration, the third optimization sub-problem is solved to obtain the optimal phase shift response vector of the reflective element in the IRS; based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the optimal phase shift response vector, the fourth optimization sub-problem is solved to obtain the optimal energy collection duration of the IRS in the first stage.

[0046] It should be noted that the system energy efficiency optimization problem is a non-convex problem. Multiple constraints and multiple variables are coupled with each other, making it difficult to solve the optimization problem directly. In order to solve the optimization problem, a low-complexity alternating optimization method is proposed, that is, the optimization problem is first converted into multiple optimization sub-problems, and then the multiple optimization sub-problems are solved in an iterative form based on the alternating optimization algorithm to obtain the optimal solution of the optimization problem.

[0047] Specifically, the energy efficiency optimization problem in the D2D communication network model is converted into a first optimization sub-problem, a second optimization sub-problem, a third optimization sub-problem and a fourth optimization sub-problem respectively.

[0048] Among them, the first optimization subproblem is used to optimize the first D2D transmit precoding in the first stage given the second D2D transmit precoding in the second stage, the phase shift response vector of the reflective element in the IRS, and the energy collection time of the IRS in the first stage; the second optimization subproblem is used to optimize the second D2D transmit precoding in the second stage given the first D2D transmit precoding in the first stage, the phase shift response vector of the reflective element in the IRS, and the energy collection time of the IRS in the first stage; the third optimization subproblem is used to optimize the phase shift response vector of the reflective element in the IRS given the first D2D transmit precoding in the first stage, the second D2D transmit precoding in the second stage, and the energy collection time of the IRS in the first stage; the fourth optimization subproblem is used to optimize the energy collection time of the IRS in the first stage given the first D2D transmit precoding in the first stage, the second D2D transmit precoding in the second stage, and the phase shift response vector of the reflective element in the IRS.

[0049] After decomposing four optimization sub-problems, the first optimization sub-problem is solved based on the initialized second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain the first optimal D2D transmit precoding in the first stage.

[0050] Furthermore, based on the first optimal D2D transmit precoding, the initialized initial phase shift response vector, and the initial energy collection duration, the second optimization sub-problem is solved to obtain the second optimal D2D transmit precoding in the second stage.

[0051] Furthermore, based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initialized initial energy collection duration, the third optimization sub-problem is solved to obtain the optimal phase shift response vector of the reflective element in the IRS.

[0052] Finally, based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector, the fourth optimization sub-problem is solved to obtain the optimal energy collection duration of the IRS in the first stage.

[0053] The embodiment of the present invention decomposes the energy efficiency optimization problem into multiple optimization sub-problems, which can simplify the problem and decouple multiple constraints and multiple variables. It further adopts an alternating optimization method to alternately fix some variables and optimize the remaining variables. It can decompose the non-convex problem into a series of relatively simple problems, which not only simplifies the complex optimization problem, but also gradually approaches the global optimal solution, thereby maximizing the system energy efficiency and improving communication performance.

[0054] According to the above content, solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration to obtain the first optimal D2D transmit precoding in the first stage includes: Through initialization, a first initial D2D transmission precoding in the first stage, a second initial D2D transmission precoding in the second stage, an initial phase shift response vector of a reflective element in an IRS, an initial energy collection duration of the IRS in the first stage, a preset threshold, and a maximum number of iterations are obtained; the first initial D2D transmission precoding, the second initial D2D transmission precoding, the initial phase shift response vector, and the initial energy collection duration are determined as first input data of the D2D communication network model; the first initial D2D transmission precoding is updated according to the first input data and a first objective function while satisfying a first constraint condition, a second constraint condition, and a third constraint condition; the first approximation The constraint condition is used to constrain the total system rate at the D2D receiver in the first stage; the second constraint condition is used to constrain the transmission power of the D2D transmitter in the first stage; the third constraint condition is used to constrain the energy collected by the IRS to be greater than or equal to the power consumption during IRS reflection; the first objective function is used to solve the first optimization subproblem; iterative execution is performed under the first constraint condition, the second constraint condition and the third constraint condition, according to the first input data and the first objective function, the step of updating the first initial D2D transmission precoding is performed until the first objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the first optimal D2D transmission precoding in the first stage.

[0055] Specifically, given ,question can be transformed into: (3) Based on fractional programming and Dinkelbach method, the above problem can be transformed into: (4) in, , the objective function is about Continuous and monotonous, The optimal solution can be expressed as: . (5) Using Lagrange dual transformation, After processing transformation, we can get (6) in, is the slack variable introduced, the problem can be rewritten as: (7) when When fixed, It can be obtained by first-order derivation as follows: (8) when When given, the secondary change technique is used to The processing changes are as follows: (9) Slack variables The optimal solution can be obtained by first-order derivative The calculation results are: (10) Further, the problem can be transformed into: (11) in, It can be calculated by formula (5), formula (8) and formula (10). The remaining problem is a semidefinite programming problem, which can be solved by the CVX toolbox.

[0056] The solution process of the first stage D2D transmission precoding based on fractional programming is shown in the following algorithm 1: (1) Initialization ,Will As the first input data of the D2D communication network model.

[0057] (2) Iterative process: Under the conditions of satisfying the first constraint, the second constraint, and the third constraint, the first input data and the problem are The first objective function is updated The specific process is: if the conditions are met , execute the update based on formula (8) , updated based on formula (10) , based on formula (5) update , based on formula (11) update ,make If the conditions are not met , reinitialize ; until .

[0058] (3) Output: .

[0059] The embodiment of the present invention solves the first optimization subproblem by combining the first initial D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration while satisfying the first constraint condition, the second constraint condition and the third constraint condition, thereby achieving decoupling of multiple constraints and multiple variables, greatly reducing the complexity of the solution algorithm, and solving the problem of maximizing the energy efficiency of the D2D communication network when the channel state information is inaccurate from the aspect of power control, thereby significantly improving the energy utilization of the D2D communication system.

[0060] According to the above content, solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration to obtain the second optimal D2D transmit precoding in the second stage includes: The first optimal D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration are determined as the second input data of the D2D communication network model; the second initial D2D transmit precoding is updated according to the second input data and the second objective function while satisfying the fourth constraint and the fifth constraint; the fourth constraint is used to constrain the total system rate at the D2D receiver in the second stage; the fifth constraint is used to constrain the transmit power of the D2D transmitter in the second stage; the second objective function is used to solve the second optimization subproblem; iteratively execute the step of updating the second initial D2D transmit precoding according to the second input data and the second objective function while satisfying the fourth constraint and the fifth constraint until the second objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the second optimal D2D transmit precoding in the second stage.

[0061] Specifically, given ,question can be transformed into: (12) Due to the existence of boundary errors in channel state information, the following two lemmas are introduced to derive relevant problem constraints.

[0062] Lemma 1: (Generalized S-procedure) is defined with respect to variables The quadratic function is as follows: (13) in, .condition Always holds true if and only if Lemma 2: (Generalized sign-definiteness) Given a set of matrices , the following inequality holds: (14) If and only if .

[0063] The interference plus noise power in equation (14c) is can be regarded as a slack variable, so formula (14b) can be reformulated as: Constraints (15) and (16) represent the useful signal power constraint and interference plus noise signal constraint under the worst channel condition, respectively. Furthermore, constraint (15) can be further processed using Grammar 1, as shown in Lemma 3 below.

[0064] Lemma 3: Substituting into constraint (15), Indicates The suboptimal solution obtained by iteration is can be approximated as its The lower bound , in, , , .

[0065] Based on Lemma 3, formula (15) can be further expressed as: (17) Based on Lemma 1 and formula (17), the following mapping relationship is defined: (18) Formula (17) can be transformed into a linear inequality (19) in, is the slack variable, .

[0066] Further, formula (16) can be transformed into a matrix inequality in, , ,Will Substituting into the above matrix inequality we can get in, , , .

[0067] definition ,Further, based on Lemma 2, formula (16) can be further expressed as: (20) in, is the slack variable introduced. can be re-expressed as: (twenty one) Introducing slack variables , and using Dinkelbach transformation, problem (20) can be transformed into: (twenty two) in, , the objective function is about is continuous and monotonic, so we have The optimal solution is: (twenty three) To further deal with problem (22), the Lagrange dual transformation is adopted. Perform the following processing: (twenty four) in, For the introduced slack variables, problem (22) is further transformed into: (25) When other variables are fixed, question (25) is about is a concave function, so by taking the derivative we can get The solution is: (26) when When fixed, the secondary transformation technique is used to After processing, we can get: (27) in, is the slack variable introduced. When other variables are fixed, The optimal solution of can be obtained by first-order derivation: (28) Furthermore, problem (24) can be further transformed into: variable It can be calculated by formula (23), formula (26) and formula (28). Question (29) is about The semidefinite programming problem can be solved using the CVX toolbox.

[0068] The solution process of the second stage D2D transmission precoding based on fractional programming is shown in the following algorithm 2: (1) Initialization ,Will And the optimal solution obtained by Algorithm 1 As the second input data of the D2D communication network model.

[0069] (2) Iteration process: Under the fourth and fifth constraints, the second input data and the problem The second objective function is updated The specific process is: if the conditions are met , execute the update based on formula (26) , updated based on formula (28) , based on formula (23) update , based on formula (29) update ,make If the conditions are not met , reinitialize ; until .

[0070] (3) Output: Optimal .

[0071] The embodiment of the present invention solves the second optimization subproblem by combining the first optimal D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration while satisfying the fourth constraint and the fifth constraint, thereby achieving decoupling of multiple constraints and multiple variables, greatly reducing the complexity of the solution algorithm, and solving the problem of maximizing the energy efficiency of the D2D communication network when the channel state information is inaccurate from the aspect of power control, thereby significantly improving the energy utilization of the D2D communication system.

[0072] According to the above content, solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the initial energy collection duration to obtain the optimal phase shift response vector of the reflective element in the IRS includes: The first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration are determined as the third input data of the D2D communication network model; under the sixth constraint condition, the initial phase shift response vector is updated according to the third input data and the third objective function; the sixth constraint condition is used to constrain the phase shift of the reflective element in the IRS; the third objective function is used to solve the third optimization subproblem; and iteratively execute the step of updating the initial phase shift response vector according to the third input data and the third objective function under the sixth constraint condition until the third objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the optimal phase shift response vector of the reflective element in the IRS.

[0073] Specifically, given ,when Given, in order to solve , introduce slack variables , the useful signal power inequality can be expressed as The linear inequality (19) can be modified as follows: (30) Further simplifying the above inequality, we can get The dimension is reduced to the following dimension: (31) Combining formula (30) and formula (31), about Problem Solving It can be further expressed as: (32) To solve the above non-convex optimization problem, we first relax the modulo 1 constraint of constraint (2f) to , the problem is further solved using a penalty-based concave-convex process. The modulo 1 constraint can be further rewritten as ,in , at a fixed point , the non-convex part can be linearized as , we further get the convex optimization problem as follows: (33) in, is the slack variable introduced. This problem is a semidefinite programming problem and can be solved using the CVX toolbox.

[0074] The solution process of IRS passive beamforming design based on penalty concave-convex process is shown in the following algorithm 3: (1) Initialization ,Will And the optimal solutions obtained by Algorithm 1 and Algorithm 2 respectively and optimal As the third input data of the D2D communication network model.

[0075] (2) Iteration process: Under the sixth constraint, according to the third input data and problem The third objective function is to update The specific process is: if the conditions are met , execute the solution problem (33) and update ,make ; If the condition is met , reinitialize ; until .

[0076] (3) Output: Optimal .

[0077] Furthermore, since the optimal It is continuous, but in fact the phase shift is discrete and needs to be restored to discrete phase shift by the following formula: (34) While satisfying the sixth constraint, the embodiment of the present invention combines the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration to solve the third optimization sub-problem, achieves decoupling of multiple constraints and multiple variables, greatly reduces the complexity of the solution algorithm, and solves the problem of maximizing the energy efficiency of the D2D communication network when the channel state information is inaccurate from the aspect of passive beamforming design, thereby significantly improving the energy utilization of the D2D communication system.

[0078] According to the above content, solving the fourth optimization subproblem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector to obtain the optimal energy collection duration of the IRS in the first stage includes: The first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the initial energy collection duration are determined as the fourth input data of the D2D communication network model; under the conditions of satisfying the third constraint and the seventh constraint, the initial energy collection duration is updated according to the fourth input data and the fourth objective function to obtain the optimal energy collection duration of the IRS in the first stage; the seventh constraint is used to constrain the IRS energy collection duration to not exceed one time slot; the fourth objective function is used to solve the fourth optimization subproblem.

[0079] Specifically, given ,when Given, the problem can be simplified to: (35) in, .

[0080] The first-order derivative of is expressed as , based on the monotonicity of the objective function, The optimal solution is expressed as: (36) The optimal solutions of Algorithm 1, Algorithm 2, and Algorithm 3 are respectively , best and optimal As the fourth input data of the D2D communication network model, under the sixth constraint condition, according to the fourth input data and the problem The fourth objective function is to solve the optimal .

[0081] While satisfying the seventh constraint, the embodiment of the present invention combines the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the initial energy collection duration to solve the fourth optimization sub-problem, achieves decoupling of multiple constraints and multiple variables, greatly reduces the complexity of the solution algorithm, and solves the problem of maximizing the energy efficiency of the D2D communication network when the channel state information is inaccurate from the aspect of energy collection time scheduling, thereby significantly improving the energy utilization of the D2D communication system.

[0082] The D2D communication system energy efficiency optimization device provided by the present invention is described below. The D2D communication system energy efficiency optimization device described below and the D2D communication system energy efficiency optimization method described above can refer to each other.

[0083] Reference Figure 3 , Figure 3 It is a structural schematic diagram of the D2D communication system energy efficiency optimization device provided by the present invention.

[0084] The D2D communication system energy efficiency optimization device comprises: The model building module 310 is used to build an IRS-assisted D2D communication network model.

[0085] The D2D communication division module 320 is used to divide the D2D communication process of the D2D communication network model in the current time slot into a first stage and a second stage; the first stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link, and the IRS collects energy from the radio frequency signal; the second stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link and an IRS reflection link.

[0086] The optimization problem solving module 330 is used to solve the energy efficiency optimization problem in the D2D communication network model, and obtain the first optimal D2D transmit precoding in the first stage, the second optimal D2D transmit precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS, and the optimal energy collection duration of the IRS in the first stage.

[0087] The energy efficiency maximization module 340 is configured to determine the maximum energy efficiency of the D2D communication system based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the optimal energy collection duration.

[0088] Furthermore, the optimization problem solving module 330 is also used for: The energy efficiency optimization problem in the D2D communication network model is respectively converted into a first optimization sub-problem, a second optimization sub-problem, a third optimization sub-problem and a fourth optimization sub-problem; the first optimization sub-problem is used to optimize the first D2D transmission precoding in the first stage given the second D2D transmission precoding in the second stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the second optimization sub-problem is used to optimize the second D2D transmission precoding in the second stage given the first D2D transmission precoding in the first stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the third optimization sub-problem is used to optimize the phase shift response vector of the reflection element in the IRS given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the energy collection time of the IRS in the first stage; the fourth optimization sub-problem is used to optimize the energy collection time of the IRS in the first stage given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the phase shift response vector of the reflection element in the IRS; Solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a first optimal D2D transmit precoding in the first stage; Solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a second optimal D2D transmit precoding in the second stage; Solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initial energy collection duration to obtain an optimal phase shift response vector of a reflective element in the IRS; Based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector, the fourth optimization sub-problem is solved to obtain the optimal energy collection duration of the IRS in the first stage.

[0089] Furthermore, the optimization problem solving module 330 is also used for: Obtaining, through initialization, a first initial D2D transmission precoding in the first stage, a second initial D2D transmission precoding in the second stage, an initial phase shift response vector of a reflective element in an IRS, an initial energy collection duration of the IRS in the first stage, a preset threshold, and a maximum number of iterations; Determine the first initial D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as first input data of the D2D communication network model; Under the conditions of satisfying the first constraint, the second constraint and the third constraint, the first initial D2D transmission precoding is updated according to the first input data and the first objective function; the first constraint is used to constrain the total system rate at the D2D receiver in the first stage; the second constraint is used to constrain the transmission power of the D2D transmitter in the first stage; the third constraint is used to constrain the energy collected by the IRS to be greater than or equal to the power consumption when the IRS is reflected; the first objective function is used to solve the first optimization subproblem; Iteratively execute the step of updating the first initial D2D transmit precoding according to the first input data and the first objective function while satisfying the first constraint condition, the second constraint condition and the third constraint condition, until the first objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the first optimal D2D transmit precoding in the first stage.

[0090] Furthermore, the optimization problem solving module 330 is also used for: Determine the first optimal D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as second input data of the D2D communication network model; Under the condition that the fourth constraint and the fifth constraint are satisfied, the second initial D2D transmit precoding is updated according to the second input data and the second objective function; the fourth constraint is used to constrain the total system rate at the D2D receiver in the second stage; the fifth constraint is used to constrain the transmit power of the D2D transmitter in the second stage; the second objective function is used to solve the second optimization subproblem; Iteratively execute the step of updating the second initial D2D transmit precoding according to the second input data and the second objective function while satisfying the fourth constraint and the fifth constraint, until the second objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, to obtain the second optimal D2D transmit precoding in the second stage.

[0091] Furthermore, the optimization problem solving module 330 is also used for: Determine the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as third input data of the D2D communication network model; Under the condition of satisfying the sixth constraint, updating the initial phase shift response vector according to the third input data and the third objective function; the sixth constraint is used to constrain the phase shift of the reflective element in the IRS; the third objective function is used to solve the third optimization sub-problem; Iteratively executing the step of updating the initial phase shift response vector according to the third input data and the third objective function while satisfying the sixth constraint condition until the third objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the optimal phase shift response vector of the reflective element in the IRS.

[0092] Furthermore, the optimization problem solving module 330 is also used for: Determining the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the initial energy collection duration as fourth input data of the D2D communication network model; Under the conditions of satisfying the third constraint and the seventh constraint, the initial energy collection duration is updated according to the fourth input data and the fourth objective function to obtain the optimal energy collection duration of the IRS in the first stage; the seventh constraint is used to constrain the IRS energy collection duration to not exceed one time slot; the fourth objective function is used to solve the fourth optimization subproblem.

[0093] It should be noted that the D2D communication system energy efficiency optimization device provided by the present invention can execute the D2D communication system energy efficiency optimization method described in any of the above embodiments during specific operation, which will not be described in detail in this embodiment.

[0094] Figure 4 is a schematic diagram of the structure of the electronic device provided by the present invention, such as Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430 and a communication bus 440, wherein the processor 410, the communication interface 420 and the memory 430 communicate with each other through the communication bus 440. The processor 410 may call the logic instructions in the memory 430 to execute the D2D communication system energy efficiency optimization method.

[0095] In addition, the logic instructions in the above-mentioned memory 430 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0096] On the other hand, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, and the computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute the D2D communication system energy efficiency optimization method provided in the above embodiments.

[0097] On the other hand, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the D2D communication system energy efficiency optimization method provided in the above embodiments is implemented.

[0098] The system embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment. Those of ordinary skill in the art may understand and implement the present embodiment without creative effort.

[0099] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A D2D communication system energy efficiency optimization method, characterized in that: include: Construct an IRS-assisted D2D communication network model; The D2D communication process of the D2D communication network model in the current time slot is divided into a first stage and a second stage; the first stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link, and the IRS collects energy from the radio frequency signal; The second stage refers to the communication process of the radio frequency signal transmitted by the D2D transmitter to the D2D receiver through the direct link and the IRS reflection link; Solving the energy efficiency optimization problem in the D2D communication network model, obtaining a first optimal D2D transmit precoding in the first stage, a second optimal D2D transmit precoding in the second stage, an optimal phase shift response vector of a reflective element in an IRS, and an optimal energy collection duration of the IRS in the first stage; The maximum energy efficiency of the D2D communication system is determined based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector, and the optimal energy collection duration.

2. The D2D communication system energy efficiency optimization method according to claim 1, characterized in that: The solving of the energy efficiency optimization problem in the D2D communication network model to obtain the first optimal D2D transmission precoding in the first stage, the second optimal D2D transmission precoding in the second stage, the optimal phase shift response vector of the reflective element in the IRS, and the optimal energy collection duration of the IRS in the first stage includes: The energy efficiency optimization problem in the D2D communication network model is respectively converted into a first optimization sub-problem, a second optimization sub-problem, a third optimization sub-problem and a fourth optimization sub-problem; the first optimization sub-problem is used to optimize the first D2D transmission precoding in the first stage given the second D2D transmission precoding in the second stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the second optimization sub-problem is used to optimize the second D2D transmission precoding in the second stage given the first D2D transmission precoding in the first stage, the phase shift response vector of the reflection element in the IRS and the energy collection time of the IRS in the first stage; the third optimization sub-problem is used to optimize the phase shift response vector of the reflection element in the IRS given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the energy collection time of the IRS in the first stage; the fourth optimization sub-problem is used to optimize the energy collection time of the IRS in the first stage given the first D2D transmission precoding in the first stage, the second D2D transmission precoding in the second stage and the phase shift response vector of the reflection element in the IRS; Solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a first optimal D2D transmit precoding in the first stage; Solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain a second optimal D2D transmit precoding in the second stage; Solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, and the initial energy collection duration to obtain an optimal phase shift response vector of a reflective element in the IRS; Based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector, the fourth optimization sub-problem is solved to obtain the optimal energy collection duration of the IRS in the first stage.

3. The D2D communication system energy efficiency optimization method according to claim 2, characterized in that: The solving the first optimization sub-problem based on the second initial D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain the first optimal D2D transmit precoding in the first stage includes: Obtaining, through initialization, a first initial D2D transmission precoding in the first stage, a second initial D2D transmission precoding in the second stage, an initial phase shift response vector of a reflective element in an IRS, an initial energy collection duration of the IRS in the first stage, a preset threshold, and a maximum number of iterations; Determine the first initial D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as first input data of the D2D communication network model; Under the conditions of satisfying the first constraint, the second constraint and the third constraint, the first initial D2D transmit precoding is updated according to the first input data and the first objective function; the first constraint is used to constrain the total system rate at the D2D receiver in the first stage; the second constraint is used to constrain the transmit power of the D2D transmitter in the first stage; the third constraint is used to constrain the energy collected by the IRS to be greater than or equal to the power consumption when the IRS is reflected; the first objective function is used to solve the first optimization subproblem; Iteratively execute the step of updating the first initial D2D transmit precoding according to the first input data and the first objective function while satisfying the first constraint condition, the second constraint condition and the third constraint condition, until the first objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the first optimal D2D transmit precoding in the first stage.

4. The D2D communication system energy efficiency optimization method according to claim 3, characterized in that: The solving the second optimization sub-problem based on the first optimal D2D transmit precoding, the initial phase shift response vector, and the initial energy collection duration to obtain the second optimal D2D transmit precoding in the second stage includes: Determine the first optimal D2D transmit precoding, the second initial D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as second input data of the D2D communication network model; Under the condition that the fourth constraint and the fifth constraint are satisfied, the second initial D2D transmit precoding is updated according to the second input data and the second objective function; the fourth constraint is used to constrain the total system rate at the D2D receiver in the second stage; the fifth constraint is used to constrain the transmit power of the D2D transmitter in the second stage; the second objective function is used to solve the second optimization subproblem; Iteratively execute the step of updating the second initial D2D transmit precoding according to the second input data and the second objective function while satisfying the fourth constraint and the fifth constraint, until the second objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, to obtain the second optimal D2D transmit precoding in the second stage.

5. The D2D communication system energy efficiency optimization method according to claim 4, characterized in that: The solving the third optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the initial energy collection duration to obtain the optimal phase shift response vector of the reflective element in the IRS includes: Determine the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the initial phase shift response vector and the initial energy collection duration as third input data of the D2D communication network model; Under the condition of satisfying the sixth constraint, updating the initial phase shift response vector according to the third input data and the third objective function; the sixth constraint is used to constrain the phase shift of the reflective element in the IRS; the third objective function is used to solve the third optimization sub-problem; Iteratively executing the step of updating the initial phase shift response vector according to the third input data and the third objective function while satisfying the sixth constraint condition until the third objective function is less than the preset threshold or the number of iterations is greater than the maximum number of iterations, so as to obtain the optimal phase shift response vector of the reflective element in the IRS.

6. The D2D communication system energy efficiency optimization method according to claim 5, characterized in that: The solving the fourth optimization sub-problem based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding and the optimal phase shift response vector to obtain the optimal energy collection duration of the IRS in the first stage includes: Determining the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the initial energy collection duration as fourth input data of the D2D communication network model; Under the conditions of satisfying the third constraint and the seventh constraint, the initial energy collection duration is updated according to the fourth input data and the fourth objective function to obtain the optimal energy collection duration of the IRS in the first stage; the seventh constraint is used to constrain the IRS energy collection duration to not exceed one time slot; the fourth objective function is used to solve the fourth optimization subproblem.

7. The D2D communication system energy efficiency optimization method according to claim 6, characterized in that: The maximum energy efficiency is determined by the following formula: ； in, represents the energy efficiency of the D2D communication system; K represents the number of D2D transmitters or the number of D2D receivers; Indicates that in the first stage, the D2D receiver The signal-to-interference-noise ratio at Indicates that in the second stage, the D2D receiver The signal-to-interference-noise ratio at Indicates that in the first stage, the D2D transmitter The transmission power; Indicates that in the second stage, the D2D transmitter The transmission power; Indicates the basic circuit power consumption of the D2D device; Indicates that in the first stage, the D2D receiver The interference plus noise power at Indicates D2D receiver To D2D transmitter A direct link channel; Indicates that in the second stage, the D2D receiver The interference plus noise power at represents the phase shift response vector of the reflective element in the IRS in the second stage; Indicates D2D receiver To D2D transmitter Cascade link channel.

8. A D2D communication system energy efficiency optimization device, characterized in that: include: A model building module, used to build an IRS-assisted D2D communication network model; A D2D communication division module is used to divide the D2D communication process of the D2D communication network model in the current time slot into a first stage and a second stage; the first stage refers to the communication process in which the radio frequency signal transmitted by the D2D transmitter is transmitted to the D2D receiver through a direct link, and the IRS collects energy from the radio frequency signal; The second stage refers to the communication process of the radio frequency signal transmitted by the D2D transmitter to the D2D receiver through the direct link and the IRS reflection link; An optimization problem solving module, used to solve the energy efficiency optimization problem in the D2D communication network model, and obtain a first optimal D2D transmit precoding in the first stage, a second optimal D2D transmit precoding in the second stage, an optimal phase shift response vector of a reflective element in an IRS, and an optimal energy collection duration of the IRS in the first stage; The energy efficiency maximization module is used to determine the maximum energy efficiency of the D2D communication system based on the first optimal D2D transmit precoding, the second optimal D2D transmit precoding, the optimal phase shift response vector and the optimal energy collection duration.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the D2D communication system energy efficiency optimization method according to any one of claims 1 to 7 are implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the D2D communication system energy efficiency optimization method according to any one of claims 1 to 7 are implemented.

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